Senior Data Engineer

The Sr. Data Engineer in our innovative team will focus on revolutionizing healthcare through AI and generative AI technologies. This role will be instrumental in designing and implementing robust data pipelines to support the development and deployment of AI models for a variety of healthcare applications. This is a critical role in transforming healthcare data into actionable insights, ensuring compliance with industry standards while leveraging cutting-edge technologies.

Data Engineering & Pipeline Development:

• Design, implement, and optimize ETL/ELT pipelines to support data ingestion and transformation from diverse healthcare data sources.
• Develop and maintain scalable data pipelines for real-time and batch processing to meet AI/ML needs.
• Work with structured, semi-structured, and unstructured data to create usable datasets for AI model training and deployment.

Database Management:

• Manage and optimize a variety of databases, including Postges, NoSQL, graph databases, and cloud-based databases like Redshift.
• Ensure efficient storage, retrieval, and integration of data across different systems.

AI Integration:

• Collaborate with data scientists and AI engineers to create datasets for a variety of use cases.
• Implement data annotation, curation, and augmentation techniques to enhance data readiness for AI/ML applications.

Healthcare Data Expertise:

• Apply knowledge of healthcare data standards such as HL7 and FHIR, ensuring adherence to HIPAA compliance and other regulatory requirements.
• Address challenges related to unstructured data extraction and large-scale data ingestion in EMR/EHR systems.

Collaboration & Innovation:

• Work closely with cross-functional teams, including healthcare specialists, to understand and address data needs.
• Ensure data quality, integrity, and security, especially when dealing with sensitive healthcare data.

Continuous Improvement:

• Stay updated with emerging technologies and frameworks in data engineering, AI, and healthcare.
• Contribute to the continuous improvement of processes and tools within the data engineering team.

Perform other duties that support the overall objective of the position

Education Required

• Bachelor’s degree (or higher) in Computer Science, Data Science, Artificial Intelligence, or a related field Or, any combination of education and experience which would provide the required qualifications for the position

Experience Required:

Proven experience in designing and building ETL/ELT pipelines.Experience working with cloud platforms like AWS, Azure, or Google Cloud.Hands-on experience preparing and managing datasets for AI/ML model training and deployment.Experience handling diverse data types and ensuring scalability in a complex environment.

Knowledge, Skills & Abilities:

• Knowledge of: Familiarity with big data frameworks such as Apache Spark, Kafka, and Hadoop. Understanding of data processing for voice, image, and text-based AI solutions. Familiarity with healthcare data standards and interoperability protocols. Knowledge of EMR/EHR systems and healthcare data management challenges.
• Skill in: Strong programming skills in Python, Scala, Java, and SQL. Excellent problem-solving and debugging skills. Strong communication. and collaboration abilities to work with diverse stakeholders.

The company has reviewed this job description to ensure that essential functions and basic duties have been included. It is intended to provide guidelines for job expectations and the employee's ability to perform the position described. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate. This document does not represent a contract of employment, and the company reserves the right to change this job description and/or assign tasks for the employee to perform, as the company may deem appropriate.